code/train_shape.py
@@ -128,13 +128,12 @@ reg_criterion = nn.MSELoss().cuda(gpu) # Regression loss coefficient alpha = 0.1 lsm = nn.Softmax() idx_tensor = [idx for idx in xrange(66)] idx_tensor = torch.FloatTensor(idx_tensor).cuda(gpu) optimizer = torch.optim.Adam([{'params': get_ignored_params(model), 'lr': args.lr}, {'params': get_non_ignored_params(model), 'lr': args.lr}], {'params': get_non_ignored_params(model), 'lr': args.lr * 10}], lr = args.lr) print 'Ready to train network.'